Semiotic study of the Japanese dry landscape garden in Ryoanji temple

http://www.ester.ee/record=b4749495*es

Nonlinear Dynamic Analysis of Long-Span Cable-Stayed Bridges with Train-Bridge and Cable Coupling

Span lengths of newly constructed cable-stayed railway bridges continue to show increases relative to those of older bridges. Accompanying such increases is the importance of ensuring that vibrations of long-span cable-stayed bridges satisfy both safety and serviceability requirements, particularly for bridges that support train passages. In contrast to modern design of bridges that support roadway vehicles, current methods for analyzing cable-stayed railway bridges do not yet typically account for coupling effects that may occur between cables and the surrounding bridge structure during train passages. This paper presents a computational framework for the nonlinear dynamic analysis of railway bridges based on a coupled train–bridge analytical model and investigates the significance of accounting for cable-related coupling effects. A case study is then carried out, where coupled dynamic responses of cables, towers, and girders of an in-service railway bridge are computed and compared to those obtained using an uncoupled approach. These comparisons demonstrate the merits of accounting for coupling phenomena when computing dynamic characteristics of cable-stayed railway bridges and highlight benefits of the coupled analysis approach in bridge design applications

Minimum BER Criterion Based Robust Blind Separation for MIMO Systems

In this paper, a robust blind source separation (BSS) algorithm is investigated based on a new cost function for noise suppression. This new cost function is established according to the criterion of minimum bit error rate (BER) incorporated into maximum likelihood (ML) principle based independent component analysis (ICA). With the help of natural gradient search, the blind separation work is carried out through optimizing this constructed cost function. Simulation results and analysis corroborate that the proposed blind separation algorithm can realize better performance in speed of convergence and separation accuracy as opposed to the conventional ML-based BSS

A Novel Blind Source Separation Algorithm and Performance Analysis of Weak Signal against Strong Interference in Passive Radar Systems

In Passive Radar System, obtaining the mixed weak object signal against the super power signal (jamming) is still a challenging task. In this paper, a novel framework based on Passive Radar System is designed for weak object signal separation. Firstly, we propose an Interference Cancellation algorithm (IC-algorithm) to extract the mixed weak object signals from the strong jamming. Then, an improved FastICA algorithm with K-means cluster is designed to separate each weak signal from the mixed weak object signals. At last, we discuss the performance of the proposed method and verify the novel method based on several simulations. The experimental results demonstrate the effectiveness of the proposed method

The high helium abundance and charge states of the interplanetary CME and its material source on the Sun

Identifying the source of the material within coronal mass ejections (CMEs) and understanding CME onset mechanisms are fundamental issues in solar and space physics. Parameters relating to plasma composition, such as charge states and He abundance (\ahe), may be different for plasmas originating from differing processes or regions on the Sun. Thus, it is crucial to examine the relationship between in-situ measurements of CME composition and activity on the Sun. We study the CME that erupted on 2014 September 10, in association with an X1.6 flare, by analyzing AIA imaging and IRIS spectroscopic observations and its in-situ signatures detected by Wind and ACE. We find that during the slow expansion and intensity increase of the sigmoid, plasma temperatures of 9 MK, and higher, first appear at the footpoints of the sigmoid, associated with chromospheric brightening. Then the high-temperature region extends along the sigmoid. IRIS observations confirm that this extension is caused by transportation of hot plasma upflow. Our results show that chromospheric material can be heated to 9 MK, and above, by chromospheric evaporation at the sigmoid footpoints before flare onset. The heated chromospheric material can transport into the sigmoidal structure and supply mass to the CME. The aforementioned CME mass supply scenario provides a reasonable explanation for the detection of high charge states and elevated \ahe\ in the associated ICME. The observations also demonstrate that the quasi-steady evolution in the precursor phase is dominated by magnetic reconnection between the rising flux rope and the overlying magnetic field structure.Comment: 10 pages, 5 figures, accepted for publication in ApJ

SuperScaler: Supporting Flexible DNN Parallelization via a Unified Abstraction

With the growing model size, deep neural networks (DNN) are increasingly trained over massive GPU accelerators, which demands a proper parallelization plan that transforms a DNN model into fine-grained tasks and then schedules them to GPUs for execution. Due to the large search space, the contemporary parallelization plan generators often rely on empirical rules that couple transformation and scheduling, and fall short in exploring more flexible schedules that yield better memory usage and compute efficiency. This tension can be exacerbated by the emerging models with increasing complexity in their structure and model size. SuperScaler is a system that facilitates the design and generation of highly flexible parallelization plans. It formulates the plan design and generation into three sequential phases explicitly: model transformation, space-time scheduling, and data dependency preserving. Such a principled approach decouples multiple seemingly intertwined factors and enables the composition of highly flexible parallelization plans. As a result, SuperScaler can not only generate empirical parallelization plans, but also construct new plans that achieve up to 3.5X speedup compared to state-of-the-art solutions like DeepSpeed, Megatron and Alpa, for emerging DNN models like Swin-Transformer and AlphaFold2, as well as well-optimized models like GPT-3

Propofol Alleviates DNA Damage Induced by Oxygen Glucose Deprivation and Reperfusion via FoxO1 Nuclear Translocation in H9c2 Cells

Ischemia/reperfusion (I/R) injury induces irreversible oxidative stress damage to the cardiac myocytes. Many studies have revealed that propofol alleviates the important organelle-mediated injury from oxidative stress in vitro. However, it remains unclear whether propofol prevents I/R-induced DNA damage in cardiomyocytes. In our study, we established an oxygen glucose deprivation/reoxygenation (OGD/R) model in H9c2 cells and found that propofol decreased reactive oxygen species (ROS) levels and suppressed cell apoptosis induced by OGD/R in H9c2 cells. In addition, propofol significantly reduced the molecular marker of DNA damage and inhibited double-strand breaks of DNA damage induced by OGD/R in H9c2 cells in a dose-dependent manner. Furthermore, we investigated the molecular mechanisms and demonstrated that propofol inhibited forkhead box O 1 (FoxO1) phosphorylation and increased FoxO1 nuclear translocation through inhibition of protein kinase B (Akt) and adenosine 5’-monophosphate-activated protein kinase (AMPK) pathways. The protective effects of propofol against oxidative stress-induced DNA damage were reversed by silencing FoxO1. Taken together, our results suggest that oxidative stress aggravates DNA damage and apoptosis in H9C2 cells, which can be reversed by propofol via FoxO1 nuclear translocation

Disproportionate increase in freshwater methane emissions induced by experimental warming

Net emissions of the potent GHG methane from ecosystems represent the balance between microbial methane production (methanogenesis) and oxidation (methanotrophy), each with different sensitivities to temperature. How this balance will be altered by long-term global warming, especially in freshwaters that are major methane sources, remains unknown. Here we show that the experimental warming of artificial ponds over 11 years drives a disproportionate increase in methanogenesis over methanotrophy that increases the warming potential of the gases they emit. The increased methane emissions far exceed temperature-based predictions, driven by shifts in the methanogen community under warming, while the methanotroph community was conserved. Our experimentally induced increase in methane emissions from artificial ponds is, in part, reflected globally as a disproportionate increase in the capacity of naturally warmer ecosystems to emit more methane. Our findings indicate that as Earth warms, natural ecosystems will emit disproportionately more methane in a positive feedback warming loop